272 Pages 20 Color & 62 B/W Illustrations
    by Chapman & Hall

    The success of individualized medicine, advanced crops, and new and sustainable energy sources requires thoroughly annotated genomic information and the integration of this information into a coherent model. A thorough overview of this field, Genome Annotation explores automated genome analysis and annotation from its origins to the challenges of next-generation sequencing data analysis.

    The book initially takes you through the last 16 years since the sequencing of the first complete microbial genome. It explains how current analysis strategies were developed, including sequencing strategies, statistical models, and early annotation systems. The authors then present visualization techniques for displaying integrated results as well as state-of-the-art annotation tools, including MAGPIE, Ensembl, Bluejay, and Galaxy. They also discuss the pipelines for the analysis and annotation of complex, next-generation DNA sequencing data. Each chapter includes references and pointers to relevant tools.

    As very few existing genome annotation pipelines are capable of dealing with the staggering amount of DNA sequence information, new strategies must be developed to accommodate the needs of today’s genome researchers. Covering this topic in detail, Genome Annotation provides you with the foundation and tools to tackle this challenging and evolving area. Suitable for both students new to the field and professionals who deal with genomic information in their work, the book offers two genome annotation systems on an accompanying downloadable resources.

    DNA Sequencing Strategies
    The Evolution of DNA Sequencing Technologies
    DNA Sequence Assembly Strategies
    Next-Generation Sequencing
    Sequencing Bias and Error Rates

    Coding Sequence Prediction
    Introduction
    Mapping Messenger RNA (mRNA)
    Statistical Models
    Cross-Species Methods
    Combining Gene Predictions
    Splice Variants

    Between the Genes
    Introduction
    Transcription Factors
    RNA
    Pseudogenes
    Other Repeats

    Genome-Associated Data
    Introduction
    Operons
    Metagenomics
    Individual Genomes

    Characterization of Gene Function through Bioinformatics: The Early Days
    Overview
    Stand-Alone Tools and Tools for the Early Internet
    Packages
    From FASTA Files to Annotated Genomes
    Conclusion

    Visualization Techniques and Tools for Genomic Data
    Introduction
    Visualization of Sequencing Data
    Visualization of Multiple Sequence Alignments
    Visualization of Hierarchical Structures
    Visualization of Gene Expression Data

    Functional Annotation
    Introduction
    Biophysical and Biochemical Feature
    Prediction
    Protein Domains
    Similarity Searches
    Pairwise Alignment Methods
    Conclusion

    Automated Annotation Systems
    Introduction
    MAGPIE
    Generic Model Organism Database (GMOD)
    AGeS
    Ensembl
    Summary

    Dynamic Annotation Systems: End-User-Driven Annotation and Visualization
    Introduction
    Web-Based Genome Annotation Browsers
    Stand-Alone Genome Annotation Browsers
    Comparative Visualization of Genomes

    Web-Based Workflows
    Introduction
    Principles of Web-Based Workflows
    Galaxy
    Taverna
    Seahawk
    Conclusion

    Analysis Pipelines for Next-Generation Sequencing Data
    Introduction
    Genome Sequence Reconstruction
    Analysis Pipelines: Case Studies
    Next-Generation Genome Browsing

    Index

    References appear at the end of each chapter.

    Biography

    Jung Soh is a research associate at the University of Calgary. He earned a Ph.D. in computer science from the University at Buffalo, The State University of New York, where he worked at the Center of Excellence for Document Analysis and Recognition (CEDAR). He also worked as a principal research scientist at the Electronics and Telecommunications Research Institute (ETRI) in Daejeon, Korea. His research interests are in bioinformatics, machine learning, and biomedical data visualization.

    Paul M.K. Gordon is the bioinformatics support specialist for the Alberta Children’s Hospital Research Institute at the University of Calgary. He has worked at the National Research Council of Canada’s Institute for Information Technology (NRC-IIT) and Institute for Marine Biosciences (NRC-IMB). His current work focuses on developing bioinformatics techniques for personalized medicine.

    Christoph W. Sensen is a professor of bioinformatics at the University of Calgary. He has previously worked as a research officer at the National Research Council of Canada’s Institute for Marine Biosciences (NRC-IMB) and as a visiting scientist at the European Molecular Biology Laboratory (EMBL) in Heidelberg. His research interests are in genome research and bioinformatics.